U.S. patent number 8,583,474 [Application Number 10/498,003] was granted by the patent office on 2013-11-12 for system and method for providing relative price point incentives based upon prior customer purchase behavior.
This patent grant is currently assigned to Catalina Marketing Corporation. The grantee listed for this patent is Ryan Carr, Gary M. Katz, Angela Clemens Kimes. Invention is credited to Ryan Carr, Gary M. Katz, Angela Clemens Kimes.
United States Patent |
8,583,474 |
Katz , et al. |
November 12, 2013 |
System and method for providing relative price point incentives
based upon prior customer purchase behavior
Abstract
The invention provides a system, computer program, and method
for generating price point based incentives comprising: determining
a category specific price point (620) associated with a dominant
competitive brand and a client brand; generating an incentive (630)
for said client brand based upon said price point and an
anticipated price differential (640).
Inventors: |
Katz; Gary M. (Northbrook,
IL), Carr; Ryan (South Elgin, IL), Kimes; Angela
Clemens (St. Louis, MO) |
Applicant: |
Name |
City |
State |
Country |
Type |
Katz; Gary M.
Carr; Ryan
Kimes; Angela Clemens |
Northbrook
South Elgin
St. Louis |
IL
IL
MO |
US
US
US |
|
|
Assignee: |
Catalina Marketing Corporation
(St. Petersburg, FL)
|
Family
ID: |
28038565 |
Appl.
No.: |
10/498,003 |
Filed: |
March 7, 2002 |
PCT
Filed: |
March 07, 2002 |
PCT No.: |
PCT/US02/06861 |
371(c)(1),(2),(4) Date: |
June 14, 2004 |
PCT
Pub. No.: |
WO03/079260 |
PCT
Pub. Date: |
September 25, 2003 |
Prior Publication Data
|
|
|
|
Document
Identifier |
Publication Date |
|
US 20050086101 A1 |
Apr 21, 2005 |
|
Current U.S.
Class: |
705/14.1 |
Current CPC
Class: |
G06Q
30/0238 (20130101); G06Q 30/0273 (20130101); G06Q
30/0283 (20130101); G06Q 30/02 (20130101); G06Q
30/0226 (20130101); G06Q 30/0222 (20130101); G06Q
30/0207 (20130101) |
Current International
Class: |
G06Q
30/00 (20120101) |
Field of
Search: |
;705/14,14.1 |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
|
|
|
|
|
|
|
WO 98/21713 |
|
May 1998 |
|
WO |
|
WO 99/12117 |
|
Mar 1999 |
|
WO |
|
Other References
Jul. 22, 2005, EPO Supplementary European Report EP 02709798. cited
by applicant .
Sep. 18, 2002, PCT International Search Report for PCT/US02/06861.
cited by applicant.
|
Primary Examiner: Lastra; Daniel
Attorney, Agent or Firm: Pillsbury Winthrop Shaw Pittman
LLP
Claims
The invention claimed is:
1. A computer system for generating price point based incentive
offers comprising: a computer system including computer memory, a
digital processing unit, and an input/output device; and POS
terminals of at least one retail store; wherein said computer
system is configured so that said digital processor stores in a
database in said computer memory transaction data for transactions
recorded by said POS terminals of said at least one retail store;
wherein said computer system is configured so that said digital
processor stores in said database an association of a dominant
competitive brand with a specified product or service category and
a client brand with said specified product or service category;
wherein said computer system is configured so that said digital
processor determines from said transaction data a price
differential between price of an item of said dominant competitive
brand and price of an item of said client brand; wherein said
computer system is configured so that said digital processor
determines from at least said price differential, a category
specific price point for said client brand; wherein said computer
system is configured so that said digital processor determines from
at least said category specific price point for said client brand,
using said digital processor, an incentive value for an incentive
offer for purchase of an item of said client brand; wherein said
computer system is configured so that said digital processor
determines from transactions in said transaction data associated
with a CID of a customer, using said digital processor, a CID
switcher determination indicating whether data associated with said
CID meets a category switcher criteria; only if said CID switcher
determination indicates transactions in said transaction data
associated with said CID meet said category switcher criteria,
using said digital processor, storing in said database said
incentive offer in association with said CID; and a transmitter for
transmitting from said computer system said incentive offer in
association with said CID to an address associated with at least
one of said CID and said at least one retail store, means for
filtering to avoid associating said determines whether each CID for
each product or service category meets category switcher criteria
for that category.
Description
This patent is a 371 national stage entry of PCT application
PCT/US02/06861, filed Mar. 7, 2002.
BACKGROUND OF THE INVENTION
1. Field of the Invention
This invention relates to the field of marketing. More
specifically, this invention relates to the field of marketing
consumer goods.
2. Discussion of the Background
Point of sale (POS) computer systems function to account for
transactions at POS terminals. POS systems typically include a
database management system including a product price look-up table
which is accessed by the POS terminal during a transaction. POS
systems retrieve to the POS terminal data defining the prices of
items for which a consumer requests purchase. POS systems total the
costs for all of those items. POS systems log the purchase of the
items. Some POS systems log the purchase of items in transaction
records also including a unique customer identification (CID)
associating that CID with the items purchased, the price of the
items purchased, and the quantity of each product item purchased,
the date of purchase, and the lane (POS terminal identification) in
which the purchase occurred.
The present inventors recognize that the data stored in some POS
computer systems can beneficially be used to determine purchase
incentives that would induce customers to purchase certain
products, as indicated below.
SUMMARY OF THE INVENTION
It is an object of this invention to determine purchase incentives
sufficient to induce customers to purchase products upon which the
incentives are offered.
It is another object of this invention to provide those purchase
incentives to the customers.
BRIEF DESCRIPTION OF THE DRAWINGS
These and other objects of the invention are explained in more
detail below with reference to the following figures.
FIG. 1 is a schematic showing a network computer system for
performing the present invention;
FIG. 2A-2C each schematically show a data structure for records in
a central database of a central computer system of the
invention;
FIG. 3 is a high level flowchart showing high level steps of the
invention;
FIG. 4 is a high level flowchart showing steps providing incentives
to customers;
FIG. 5 is a medium level flowchart showing steps for analyzing
transaction data for step 330 in FIG. 3; and
FIG. 6 is a medium level flowchart showing steps for generating
incentive data for step 340 in FIG. 3.
DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION
FIG. 1 shows a computer network system 1. System 1 preferably
includes central computer system 11, central database 12, Internet
13, retailer1 computer system 14, retailer1 database 15, retailer2
computer system 16, retailer2 database 17, retailer3 computer
system 18, and retailer3 database 19.
In addition, system 1 may include customer computer 5, manufacturer
computer system 6, and manufacturer database 7.
While shown with one central computer system and three retailer
computer systems, the present invention may also function with
either a single computer system performing all of the functions
that are specified below or the single central computer system 11
and a single retailer computer system (one of 14, 16, 18).
Each of the noted computer systems 6, 11, 14, 16, and 18 preferably
include hardware and software enabling them to exchange data via
the Internet 13. Each of the aforementioned computer Systems is
indicated as connected to Internet 13 via a communication line. The
communication lines may be electrical, optical, or wireless based
lines. The data communication need not be over the Internet.
Each of the databases 7, 12, 15, 17, and 19 preferably are
relational computer database systems in which data is stored in
sets of fields associated with one another, referred to as records,
and in which data of the same type, e.g., field, is stored in a
common format and in association with a field name. Field names are
optional. Each set of records and fields having the same types of
associations is called a table. Each of the aforementioned
databases may have a plurality of tables. Each of those tables may
include one or more fields the concatenation of which provides a
unique identification of that record in that table. Those unique
identifications are referred to as primary keys. Each of the tables
may include a field which is a primary key in a different table,
which field is referred to in the subject table as a foreign key.
Preferably, each of the database management systems includes
associated software enabling a plurality of software functions to
be performed on the records and tables in the database, including
sorting, summing, and selecting, preferably based upon the
structured query language (SQL) standard database language.
Each of the aforementioned computer systems preferably includes at
least one digital processor and hardware for inputting and
outputting data and inputting control signals.
Retailer databases 15, 17, and 19 are each representative of
databases of a retailers POS systems. Each one of those databases
preferably includes transaction records for transactions recorded
by the POS terminals (lanes), in the corresponding retail store or
stores. In this regard, each of the retailer computer systems 14,
16, 18, may represent the computer POS system for a single store or
a plurality of associated stores.
Central database 12 stores transaction data from various ones of
the retailers. The transaction data stored in central database 12
corresponds to transaction data stored in each one of the retailer
databases 15, 17, 19.
FIGS. 2A-2C illustrate alternative data structures of transaction
data records stored in the central database 12.
FIG. 2A shows record format 200 including records illustrated by
rows including field name record 210, data record 211, and data
record 212. Data structure 200A also shows columns illustrating
data fields including the store ID field 213, the customer ID field
214, the transaction date field 215, the lane ID field 216, the
UPC1 field 217A, the UPC1 price field 217B, the UPC2 field 218A,
and the UPC2 price field 218B. In addition, the data structure 200A
would include additional pairs of UPC and price fields for all UPCs
corresponding to products sold in the corresponding store or stores
controlled by one of the retailer computer systems 14, 16, 18. The
UPC1 field stores the number of product items having UPC code UPC1
in the transaction associated with the data record. The UPC1 price
field stores a price associated with the UPC1 product items
purchased in the transaction; either the per unit price, the
average per unit price, or the total price for all product items
having UPC code UPC1.
FIG. 2B shows data structure 200B including the same columns 213,
214, 215, and 216 as in FIG. 2A. The data structure in 200B differs
from the data structure 200A in the manner in which the product
transaction data is stored. Specifically, field 217C stores in a
single field a UPC code of a first product purchased, the number of
units of that product purchase, and an associated price for the
purchase of the units of that product. Field 218C stores UPC code,
number of units purchases, and associated price for the next
product contained in the same transaction record. Additional fields
would contain UPC codes, number of units purchased, and associated
price for each of the remaining products contained in the
transaction record Elements 210B, 211B, and 212B, correspond to
elements 210, 211, and 212, differing only in the naming of the
field headings 217C, 218C, and corresponding data for product items
contained in the transactions.
FIG. 2C shows data structure 200C presenting yet another means in
which the same data shown in the data structures 200A and 200B can
be stored. In data structure 200C all data for products purchased,
the number of units of the products purchased, and associated
prices are stored in a data delimited form in the single data field
217A. In this format, the triplet of product UPC code, number of
units purchased, and associated price are separated from the next
triplet by a field delimiter, shown here to be a semi colon, and
each member of the triplet is separated from one another by another
delimiter, shown here to be a comma.
Data records 200A-200C illustrate alternative data structures in
which transaction data can be stored. One skilled in data base
design will recognize that there are other data structures that may
be used to store the same data. In addition, the TransDate field
may contain both date and time of day data.
Embodiments of the method of the invention are specified in
connection with FIGS. 3-6.
The following definitions are useful in specifying the methods of
the invention.
A product or service category as used herein means a group of
products or services that have a similar set of characteristics
such that they may be considered to provide consumers
interchangeable utility. Examples of categories of products are
tomato sauce, cold cereal, canned beans, and deodorants.
A purchase cycle is defined herein to mean the average or medium
period of time between purchases of products associated with a CID,
or a store D and a CID. That is, the average time between purchases
of goods associated with either the same consumer or consumers that
use the same CID, such as members of a household or family.
A category specific purchase cycle is defined herein to mean the
average, median, or range of time centered about either the average
or median times between purchase of goods in a specified category
in association with a CID, or a store ID and a CID. The category
specific purchase cycle is a prediction of the time between when a
consumer purchases products from the specified category.
A category specific price point is defined herein to mean a
difference in price between two brands of products in the same
category at which purchases (by consumers) associated with a CID,
or with a store ID and a CID are statistically equally likely to be
for either of the two brands of products.
FIG. 3 shows steps involved in recording and analyzing transaction
data.
In step 310, a retailer's POS system records transaction data. The
transaction data typically includes a customer ID, a transaction
date and time, a lane specification, and the UPC codes, number of
units of that UPC code that are contained in the trasaction, and
the associated price, for each product item in a transaction.
Preferably, the transaction record includes a CID.
This invention relates to those transaction records which do
include a CID. The transaction record may include a store ID.
However, store IDs may be associated with records received by the
central computer system 11 when the central computer system
receives records from a specified retailer computer system, such as
retailer computer systems 14, 16, or 18.
In step 320, a retailer computer system transmits transaction data
to the central computer system 11. The central computer system 11
stores that transaction data in the central data base 12.
In step 330, the central computer system 11 analyzes the
transaction data. Results of that analysis include records which
contain either a CID or a store ID and a CID. Each record also
includes data indicating at least one category and an associated
category specific price point. Each record preferably also includes
at least one of data indicating a purchase cycle and a category
specific purchase cycle for the specified category.
In step 340, the central computer system 11 generates incentive
data. The incentive data includes data associated with a CID, and
preferably data specifying discounts contingent upon the purchase
of specified products. Typically, the incentive data is also stored
in association with at least one of a store ID and a retailer chain
ID.
In step 350, the retail computer system transmits the incentive
data relating to transaction data from a specified retail store or
association of stores to the corresponding retailer computer system
14, 16, 18 either for one or a plurality of CIDs. Preferably, the
corresponding retail computer system stores the incentive data in
the corresponding retailer database 15, 17, or 19. However, if the
CID relates to a transaction in process, the data may used by the
CPU of the retailer computer system or the CPU, if any, of a smart
POS terminal, in processing that transaction. Thus, in some
embodiments, the incentive data need not be stored in the database
15, 17, 19.
FIG. 4 shows steps involved in providing incentives to the customer
during a transaction in a retail store. Alternatively, the
incentives could be provided via postal mail, via email, or via any
other communication medium.
In step 400, the retail computer system 14, 16, or 18, records a
CID, preferably at a POS terminal. That recording may occur during
a customer's transaction in which the customer is purchasing
products. However, the retail computer system may record the
customers' CID at any time. For example, the retailer's computer
system may record the CID in response to receipt of that CID
transmitted from the customer computer 5 over the Internet 13 to
the retailer computer system. In addition, one or more CIDs may be
transmitted by the manufacturer computer system 6 to any one of the
retailer computer systems 14, 16, 18.
Furthermore, either the manufacturer computer system 6 or the
customer computer 5 may transmit one or more CIDs and one or more
retailer computer system identifications to the central system 11.
In response, the central computer system 1 may generate incentive
data and transmit the incentive data to the corresponding retailer
computer system, or to the manufacturer computer system 6. In
addition, the central computer system 11 may transmit the incentive
data for a specific consumer (as indicated for example by a CD
associated with a network address for the customer's computer 5) to
that consumer's customer computer 5. The incentive data may
specify, or whichever computer system to which that data is sent
may contain means for, printing that data in either or both of
machine readable and human readable form. That is, the incentive
data may be printed or stored in the form of vouchers or coupons
providing discounts to the specified CID for purchases of one or
more specified products.
In step 420, the retailer computer system controlling the POS
terminal at which the CID has been recorded, typically but not
necessarily in association with a purchase transaction at the POS
terminal, determines whether the CID qualifies for incentives.
In step 421, assuming the answer to the determination in step 420
was yes, the retailer computer system provides incentive to the
customer. The POS terminal or an associated device generates the
incentive so that it can be provided to the person holding the CID.
It may be the central computer system 11 instead of a retailer
computer system which performs step 420 during the customer's
transaction.
In step 422, the retailer computer system completes the customer's
transaction at the point of sale terminal and awaits the next
transaction. This step involves the storing of the customer's
transaction record for the current transaction.
FIG. 5 shows steps involved in analyzing data. In overview, FIG. 5
shows a flowchart including four nested loops. The outermost loop
involves retrieving from memory the next customer ID. The
intermediate loop involves retrieving from memory the next
category. The two inner loops involve determining whether data
associated with a CID indicates that the CID corresponds to
category switcher purchase behavior and, if category switcher
behavior exists, whether the purchase data meets filters indicating
that the incentives for the associated CID should be price
based.
In step 510, the central computer system 11 retrieves the next
customer ID.
In step 520, the central computer system 11 receives the next
product category.
In step 530, the central computer system determines whether the
CID's transaction for products in the current category retrieved in
step 520 meets category switcher criteria. If the CID's transaction
data for that category does not meet category switcher criteria,
the processing loops back to step 520 and retrieves the next
category. If the CID's transaction data for that category does meet
switcher criteria for that category, processing continues to step
540.
A client brand is defined herein to mean a brand of a manufacturer
associated with an incentive program for execution by the central
computer system 11.
A competitive brand of a specified category is defined herein to
mean a brand of a product associated with that category made by
other than the manufacturer of the client brand. Typically, the
specified manufacturer is an entity requesting services from the
entity owning the central computer system 11 disclosed herein. For
example, the specific manufacturer may be a manufacturer requesting
the owner of the central computer system 11 to perform a customer
category specific price point marking program as disclosed in this
application.
A dominant competitive brand in a specified category is defined
herein to mean a brand, other than the client brand, for which
there are associated with the current CID the most purchases (as
measured either in number of units purchased or dollar value of
purchases or number of times a shopper goes to a store and buys in
the specified category, referred to herein as category trips) in
the product category over a specified period of time. Preferably,
that specified period of time is at least two months, more
preferably at least six months and more preferably at least about
one year. Preferably, that specified period of time extends up to
the present time, or to within about one, two, or three weeks of
the present time.
Step 530 involves the sub-steps of (1) determining the dominant
competitive brand in the specified category for the current CID and
(2) determining whether the CID's purchase behavior with respect to
the dominant competitive brand and the client brand or brands meets
category switcher criteria. The client brand may be specified. The
central database 12 may store a table or file listing the product
brands for each one of a plurality of product categories.
Preferably, the dominant competitive brand for the specified
category is defined to be the brand of product other than the
client brand for which either the largest number of units or the
largest number of dollars of purchases exists in the transaction
records associated with the current customer ID being analyzed in
step 530. While the dominant competitive brand and the client brand
definitions refer specifically to step 530, the method of analyzing
the data need not be limited to algorithm specifically shown and
discussed with respect to FIG. 5. For example, the loops retrieving
CIDs and categories can be inverted without affecting the results
of the analysis shown in FIG. 5.
In step 540, central computer system 11 determines whether the
CID's transaction data meets certain filter criteria. If the CID's
transaction data for the specified category does meet the filter
criteria, processing returns to step 520 and the next category is
retrieved.
Filter criteria are criteria indicating that providing to a
customer holding a card storing the CID incentives based upon price
point data would be ineffective, either because of lack of price
point sensitivity or because the incentives would interfere with a
sponsoring manufacturer's anticipated sales. Thus, one filter is
criteria indicating lack of price sensitivity between the dominant
competitive and client brands. Another filter is criteria
indicating that the dominant competitive and client brands for the
specified category are both made by the same manufacturer. That is,
customer loyalty to a manufacturer for a specified category is a
filter which returns processing from step 540 back to step 520 to
retrieve the next category. Another filter is data showing the
customer's tendency to purchase different brands in the same
product category during the same purchase. This purchase behavior
shows a lack of price point sensitivity. Purchasing in multiple
brands for products in the same category during the same purchase
transaction is a filter which returns processing from step 540 back
to step 520 to retrieve the next category.
In step 540, if no filter criteria are met, processing proceeds to
step 550.
In step 550, central computer system 11 determines the category
specific price points between the dominant competitive and client
brands for the CID and specified category. For example, the CID's
transaction data in the hand soap category may indicate that the
dominant competitive brand is Dial brand soap. The client brand may
be Ivory brand soap. The CID's transaction data for the hand soap
category may indicate that the customer purchases Dial soap
whenever Dial soap is no more than 20 cents more expensive than
Ivory soap, per 4 ounce bar of soap. In such an example, the price
point is 20 cents favoring Dial over Ivory. Preferably, the period
of time extends from the current time back from between a few
months, preferably greater than six months, and preferably up to
one year.
Price point determinations are preferably based upon price data for
the dominant competitive and client brands in the specified
category in a specified store at the time of each transaction being
analyzed in step 530. Price data for all products is preferably
obtained from the transaction records transmitted from the retail
store to the central computer system 11. The data for the price of
both the dominant competitive and the client brands in a specified
store at a specified time may be determined by the central computer
system 11 by reviewing data for additional customer records
corresponding to purchases made in the corresponding retail store
for both the dominant competitive and client brands. Alternatively,
price data for all product brands sold in a store may be
periodically or intermittently transmitted from each retailer
computer system 14, 16, 18 to the central computer system 11. In
addition, the central computer system 11 may use any of the
foregoing sources of product price data at various times to predict
product brand price variations and future prices in a specific
retail store as a function of time.
In step 560, the central computer system 11 determines the category
specific purchase cycle. For example, the central computer system
11 might determine that the CID associated with a specified
customer and a specified retail store purchases hand bar soap most
probably in the range of two to four weeks after the most recent
prior purchase. In this example, the purchase cycle in the hand bar
soap category for this specified customer ID would be set at
between two and four weeks, preferably at three weeks.
FIG. 6 illustrates steps involved in the central computer system 11
in generating incentive data.
In step 610, the central computer system retrieves the next pair of
CID and category.
In step 620, the central computer system 11 determines for the
retrieved CID and category whether price point and purchase cycle
data are present. If no price point and purchase cycle data is
present, processing returns to step 610 to retrieve the next CID)
and category combination. If price point and purchase cycle data
exist for the current CID and product category, processing proceeds
to step 630.
In step 630, the central computer system 11 anticipates the price
differential between the dominant competitive and client brand in
the specified category at a time indicated by the purchase cycle
data when the customer associated with the current customer ID is
likely to next purchase products in the specified category. The
anticipation may of course be based upon the current or recent past
price differential. The anticipation may be based upon
interpolating using annual cyclical price variations, or by
extrapolating based upon recent trends (less than one year) in
prices. Extrapolation for example may employ linear regression
analysis.
In step 640, the central computer system 11 determines an incentive
value based upon the price differential anticipated in step 630 and
the price point determined in step 550. The incentive is preferably
a discount contingent upon purchase of the client brand during a
specified period of time. In addition, in step 640, the central
computer system may also determine when or during what period of
time to offer the customer associated with the current specified
CID the foregoing incentive. The price point based incentives for a
category may be offered from the current time until the end of the
calculated purchase cycle, at a time corresponding to a few days
around the mid point of the category specific purchase cycle, or
near the end of a category specific purchase cycle.
The incentive determined in step 640 may be offered to the customer
either via transmission over the Internet to an address associated
with the CID, such as the customer's email address, often
associated with the customer computer 5, to a personal web page
(i.e., a web site address for which the file associated therewith
is programmed to display graphics or information preselected by the
person associated with the CID) associated with a CID, to the
retailer computer system 14, 16, or 18 associated with the retailer
ID and customer ID, or to the manufacturer computer system 6. If
the central computer system 11 transmits the incentive data to one
of the retailer computer systems 14, 16, 18, then the retailer
computer systems can provide the corresponding incentive to the
customer associated with the CD when the customer next presents the
CID at a POS terminal.
The invention also comprises a computer program product storing
programming to implement the steps of the invention.
Obviously, numerous modifications and variations of the present
invention are possible in light of the above teachings. It is
therefore to be understood that within the scope of the appended
claims, the invention may be practiced otherwise than as
specifically described herein.
* * * * *